Evidence map›Paper›PMID 20680318›Full record

ReviewInternational journal of legal medicine2010

Laser capture microdissection in forensic research: a review.

Mado Vandewoestyne, Dieter Deforce

Open access · hybridAbstract readReview
In one paragraph

Review in International journal of legal medicine, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
2.3field-weighted citation impact, top 12% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

19 citing papers in PubMed, 81 citations in OpenAlex.

  1. Trial
  2. Review
  3. Article
  4. Article
  5. Review
  6. Article
  7. Article
  8. Article
  9. Article
  10. Review
  11. Article
  12. Article
  13. Article
  14. Technologies for Single-Cell Isolation.International journal of molecular sciences · 2015
    Review
  15. Article
  16. Article
  17. Forensic DNA research: keeping it real.International journal of legal medicine · 2012
    Article
  18. Review
  19. Transcriptome analysis of single cells.Journal of visualized experiments : JoVE · 2011
    Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

2 authors at 1 institution in 1 country.

Mado VandewoestyneLaboratory of Pharmaceutical Biotechnology, Faculty of Pharmaceutical Sciences, Ghent University, Harelbekestraat 72, 9000, Ghent, Belgium.
Dieter Deforce
Ghent University · BE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In forensic sciences, short tandem repeat (STR) analysis has become the prime tool for DNA-based identification of the donor(s) of biological stains and/or traces. Many traces, however, contain cells and, hence, DNA, from more than a single individual, giving rise to mixed genotypes and the subsequent difficulties in interpreting the results. An even more challenging situation occurs when cells of a victim are much more abundant than the cells of the perpetrator. Therefore, the forensic community seeks to improve cell-separation methods in order to generate single-donor cell populations from a mixed trace in order to facilitate DNA typing and identification. Laser capture microdissection (LCM) offers a valuable tool for precise separation of specific cells. This review summarises all possible forensic applications of LCM, gives an overview of the staining and detection options, including automated detection and retrieval of cells of interest, and reviews the DNA extraction protocols compatible with LCM of cells from forensic samples.

Indexed as

LasersResearch DesignBiometric IdentificationCell SeparationDNA FingerprintingEquipment DesignFemaleFlow CytometryForensic PathologyHumansMaleMicrodissectionSemenSex OffensesSpermatozoaViolence

Identifiers

PMID20680318
PMCPMC2952761
OpenAlexW1991039031

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.